Northforge retasks one cell across three lines
Practical notes on building, validating, and scaling physical-AI fleets.
How operators used Foremai to train skills in simulation and orchestrate mixed fleets, with the numbers to show for it.
Operators with measurable Foremai results
Deep dives into how teams got to value.
Practical notes on building, validating, and scaling physical-AI fleets.
Practical notes on building, validating, and scaling physical-AI fleets.
Practical notes on building, validating, and scaling physical-AI fleets.
Practical notes on building, validating, and scaling physical-AI fleets.
Practical notes on building, validating, and scaling physical-AI fleets.
Practical notes on building, validating, and scaling physical-AI fleets.
By training changeover skills overnight in simulation, Northforge turned a single-purpose cell into a flexible one.
One agentic planner assigns and de-conflicts arms and AMRs so throughput holds when volume spikes.
“Foremai made a rigid cell flexible. That changed our whole capex conversation.”
“At peak, the fleet just kept flowing. The planner earned its keep.”
“Zero crashes on go-live is not normal. With Foremai it was.”
Common threads across successful deployments.
Every success started by validating skills in the twin before touching hardware, then compounding them across sites.
One high-ROI cell first.
Line, then site, then org.
Cost-per-task from day one.
Robots act in the physical world, so every skill is validated before it ever touches hardware.
Every policy must pass success + collision + force limits in sim before deploy.
AES-256 at rest, TLS 1.3 in transit, per-site key isolation.
Run in your VPC or on-prem; telemetry never leaves your boundary.
SAML/OIDC, provisioning, and role-based access down to the cell.
Vendor-agnostic across robots, controllers, and systems of record.
Book a demo and let’s map your path to measurable results.